SweetNET: A Bioinformatics Workflow for Glycopeptide MS/MS Spectral Analysis

MS-based glycomics and glycoproteomics methods enabling isomeric characterization

Glycosylation is one of the most significant and abundant posttranslational modifications in mammalian cells. It mediates a wide range of biofunctions, including cell adhesion, cell communication, immune cell trafficking, and protein stability. Also, aberrant glycosylation has been associated with various diseases such as diabetes, Alzheimer's disease, inflammation, immune deficiencies, congenital disorders, and cancers. The alterations in the distributions of glycan and glycopeptide isomers are involved in the development and progression of several human diseases. However, the microheterogeneity of glycosylation brings a great challenge to glycomic and glycoproteomic analysis, including the characterization of isomers. Over several decades, different methods and approaches have been developed to facilitate the characterization of glycan and glycopeptide isomers. Mass spectrometry (MS) has been a powerful tool utilized for glycomic and glycoproteomic isomeric analysis due to its high sensitivity and rich structural information using different fragmentation techniques. However, a comprehensive characterization of glycan and glycopeptide isomers remains a challenge when utilizing MS alone. Therefore, various separation methods, including liquid chromatography, capillary electrophoresis, and ion mobility, were developed to resolve glycan and glycopeptide isomers before MS. These separation techniques were coupled to MS for a better identification and quantitation of glycan and glycopeptide isomers. Additionally, bioinformatic tools are essential for the automated processing of glycan and glycopeptide isomeric data to facilitate isomeric studies in biological cohorts. Here in this review, we discuss commonly employed MS-based techniques, separation hyphenated MS methods, and software, facilitating the separation, identification, and quantitation of glycan and glycopeptide isomers.

Methods for quantification of glycopeptides by liquid separation and mass spectrometry

Recent advances in analytical techniques provide the opportunity to quantify even low-abundance glycopeptides derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Herein, we discuss the sample preparation procedures and the mass spectrometry (MS) strategies that have facilitated glycopeptide quantification, as well as the standards used for glycopeptide quantification. For sample preparation, various glycopeptide enrichment methods are summarized including the columns used for glycopeptide separation in liquid chromatography separation. For MS analysis strategies, MS1 level-based quantification and MS2 level-based quantification are described, either with or without labeling, where we have covered isotope labeling, TMT/iTRAQ labeling, data dependent acquisition, data independent acquisition, multiple reaction monitoring, and parallel reaction monitoring. The strengths and weaknesses of these methods are compared, particularly those associated with the figures of merit that are important for clinical biomarker studies and the pathological and functional studies of glycoproteins in various diseases. Possible future developments for glycopeptide quantification are discussed.

GlycoSLASH: Concurrent Glycopeptide Identification from Multiple Related LC-MS/MS Data Sets by Using Spectral Clustering and Library Searching

Liquid chromatography coupled with tandem mass spectrometry is commonly adopted in large-scale glycoproteomic studies involving hundreds of disease and control samples. The software for glycopeptide identification in such data (e.g., the commercial software Byonic) analyzes the individual data set and does not exploit the redundant spectra of glycopeptides presented in the related data sets. Herein, we present a novel concurrent approach for glycopeptide identification in multiple related glycoproteomic data sets by using spectral clustering and spectral library searching. The evaluation on two large-scale glycoproteomic data sets showed that the concurrent approach can identify 105%-224% more spectra as glycopeptides compared to the glycopeptide identification on individual data sets using Byonic alone. The improvement of glycopeptide identification also enabled the discovery of several potential biomarkers of protein glycosylations in hepatocellular carcinoma patients.

Site-specific glycosylation of proteoglycans: a revisited frontier in proteoglycan research

Proteoglycans (PGs), a class of carbohydrate-modified proteins, are present in essentially all metazoan organisms investigated to date. PGs are composed of glycosaminoglycan (GAG) chains attached to various core proteins and are important for embryogenesis and normal homeostasis. PGs exert many of their functions via their GAG chains and understanding the details of GAG-ligand interactions has been an essential part of PG research. Although PGs are also involved in many diseases, the number of GAG-related drugs used in the clinic is yet very limited, indicating a lack of detailed structure-function understanding. Structural analysis of PGs has traditionally been obtained by first separating the GAG chains from the core proteins, after which the two components are analyzed separately. While this strategy greatly facilitates the analysis, it precludes site-specific information and introduces either a "GAG" or a "core protein" perspective on the data interpretation. Mass-spectrometric (MS) glycoproteomic approaches have recently been introduced, providing site-specific information on PGs. Such methods have revealed a previously unknown structural complexity of the GAG linkage regions and resulted in identification of several novel CSPGs and HSPGs in humans and in model organisms, thereby expanding our view on PG complexity. In light of these findings, we discuss here if the use of such MS-based techniques, in combination with various functional assays, can also be used to expand our functional understanding of PGs. We have also summarized the site-specific information of all human PGs known to date, providing a theoretical framework for future studies on site-specific functional analysis of PGs in human pathophysiology.

Recent advancements in glycoproteomic studies: Glycopeptide enrichment and derivatization, characterization of glycosylation in SARS CoV2, and interacting glycoproteins

Proteomics studies allow for the determination of the identity, amount, and interactions of proteins under specific conditions that allow the biological state of an organism to ultimately change. These conditions can be either beneficial or detrimental. Diseases are due to detrimental changes caused by either protein overexpression or underexpression caused by as a result of a mutation or posttranslational modifications (PTM), among other factors. Identification of disease biomarkers through proteomics can be potentially used as clinical information for diagnostics. Common biomarkers to look for include PTM. For example, aberrant glycosylation of proteins is a common marker and will be a focus of interest in this review. A common way to analyze glycoproteins is by glycoproteomics involving mass spectrometry. Due to factors such as micro- and macroheterogeneity which result in a lower abundance of each version of a glycoprotein, it is difficult to obtain meaningful results unless rigorous sample preparation procedures are in place. Microheterogeneity represents the diversity of glycans at a single site, whereas macroheterogeneity depicts glycosylation levels at each site of a protein. Enrichment and derivatization of glycopeptides help to overcome these limitations. Over the time range of 2016 to 2020, several methods have been proposed in the literature and have contributed to drastically improve the outcome of glycosylation analysis, as presented in the sampling surveyed in this review. As a current topic in 2020, glycoproteins carried by pathogens can also cause disease and this is seen with SARS CoV2, causing the COVID-19 pandemic. This review will discuss glycoproteomic studies of the spike glycoprotein and interacting proteins such as the ACE2 receptor.

Glyco-Decipher enables glycan database-independent peptide matching and in-depth characterization of site-specific N-glycosylation

Glycopeptides with unusual glycans or poor peptide backbone fragmentation in tandem mass spectrometry are unaccounted for in typical site-specific glycoproteomics analysis and thus remain unidentified. Here, we develop a glycoproteomics tool, Glyco-Decipher, to address these issues. Glyco-Decipher conducts glycan database-independent peptide matching and exploits the fragmentation pattern of shared peptide backbones in glycopeptides to improve the spectrum interpretation. We benchmark Glyco-Decipher on several large-scale datasets, demonstrating that it identifies more peptide-spectrum matches than Byonic, MSFragger-Glyco, StrucGP and pGlyco 3.0, with a 33.5%-178.5% increase in the number of identified glycopeptide spectra. The database-independent and unbiased profiling of attached glycans enables the discovery of 164 modified glycans in mouse tissues, including glycans with chemical or biological modifications. By enabling in-depth characterization of site-specific protein glycosylation, Glyco-Decipher is a promising tool for advancing glycoproteomics analysis in biological research.

Poor peptide fragmentation and unusual glycan structures limit mass spectrometry-based analysis of intact N-glycopeptides. Here, the authors develop Glyco-Decipher, a glycan-independent peptide search tool, to tackle these issues and improve the coverage of site-specific glycan analysis.

Glycomic and Glycoproteomic Techniques in Neurodegenerative Disorders and Neurotrauma: Towards Personalized Markers

The proteome represents all the proteins expressed by a genome, a cell, a tissue, or an organism at any given time under defined physiological or pathological circumstances. Proteomic analysis has provided unparalleled opportunities for the discovery of expression patterns of proteins in a biological system, yielding precise and inclusive data about the system. Advances in the proteomics field opened the door to wider knowledge of the mechanisms underlying various post-translational modifications (PTMs) of proteins, including glycosylation. As of yet, the role of most of these PTMs remains unidentified. In this state-of-the-art review, we present a synopsis of glycosylation processes and the pathophysiological conditions that might ensue secondary to glycosylation shortcomings. The dynamics of protein glycosylation, a crucial mechanism that allows gene and pathway regulation, is described. We also explain how-at a biomolecular level-mutations in glycosylation-related genes may lead to neuropsychiatric manifestations and neurodegenerative disorders. We then analyze the shortcomings of glycoproteomic studies, putting into perspective their downfalls and the different advanced enrichment techniques that emanated to overcome some of these challenges. Furthermore, we summarize studies tackling the association between glycosylation and neuropsychiatric disorders and explore glycoproteomic changes in neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington disease, multiple sclerosis, and amyotrophic lateral sclerosis. We finally conclude with the role of glycomics in the area of traumatic brain injury (TBI) and provide perspectives on the clinical application of glycoproteomics as potential diagnostic tools and their application in personalized medicine.

LvCPG2 facilitated WSSV infection by interaction with VP26 and VP28

Chondroitin sulfate proteoglycans (CSP), widely distributed in extracellular matrices, have several important functions in vertebrates. In certain viruses, CSP acts as a receptor to promote infection. However, chondroitin proteoglycans lack sulfate are poorly understood in invertebrates. In this study, chondroitin proteoglycan 2 of Litopenaeus vannamei (LvCPG2) was cloned. The open reading frame of LvCPG2 cDNA is 2133 bp, which encodes a protein of 710 amino acids. LvCPG2 contained eight Chitin-binding domain type 2 (ChtBD2). LvCPG2 had the highest expression in lymphoid and significantly increased after WSSV challenge. The relative expression of IE1 and VP28, as well as the viral copy numbers were decreased significantly in LvCPG2-silenced shrimp. The far-western blotting result showed that LvCPG2 interacted with VP26 and VP28. Molecular docking complexes showed that N-terminal of LvCPG2 interacted with C-terminal VP26, while C-terminal of LvCPG2 combined with N-terminal of VP28. Flow cytometry analysis indicated that LvCPG2 could facilitate WSSV adhesion and penetration of shrimp hemocytes. Collectively, these findings suggested that LvCPG2 was involved in WSSV infection by interaction with VP26 and VP28.

Expanding the Chondroitin Sulfate Glycoproteome - But How Far?

Chondroitin sulfate proteoglycans (CSPGs) are found at cell surfaces and in connective tissues, where they interact with a multitude of proteins involved in various pathophysiological processes. From a methodological perspective, the identification of CSPGs is challenging, as the identification requires the combined sequencing of specific core proteins, together with the characterization of the CS polysaccharide modification(s). According to the current notion of CSPGs, they are often considered in relation to a functional role in which a given proteoglycan regulates a specific function in cellular physiology. Recent advances in glycoproteomic methods have, however, enabled the identification of numerous novel chondroitin sulfate core proteins, and their glycosaminoglycan attachment sites, in humans and in various animal models. In addition, these methods have revealed unexpected structural complexity even in the linkage regions. These findings indicate that the number and structural complexity of CSPGs are much greater than previously perceived. In light of these findings, the prospect of finding additional CSPGs, using improved methods for structural and functional characterizations, and studying novel sample matrices in humans and in animal models is discussed. Further, as many of the novel CSPGs are found in low abundance and with not yet assigned functions, these findings may challenge the traditional notion of defining proteoglycans. Therefore, the concept of proteoglycans is considered, discussing whether "a proteoglycan" should be defined mainly on the basis of an assigned function or on the structural evidence of its existence.

ANALYSIS OF CARBOHYDRATES AND GLYCOCONJUGATES BY MATRIX-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY: AN UPDATE FOR 2015-2016

This review is the ninth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2016. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented over 30 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show no sign of deminishing. © 2020 Wiley Periodicals, Inc.

Recent Advances in Software Tools for More Generic and Precise Intact Glycopeptide Analysis

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

Calculating Glycoprotein Similarities From Mass Spectrometric Data

Complex protein glycosylation occurs through biosynthetic steps in the secretory pathway that create macro- and microheterogeneity of structure and function. Required for all life forms, glycosylation diversifies and adapts protein interactions with binding partners that underpin interactions at cell surfaces and pericellular and extracellular environments. Because these biological effects arise from heterogeneity of structure and function, it is necessary to measure their changes as part of the quest to understand nature. Quite often, however, the assumption behind proteomics that posttranslational modifications are discrete additions that can be modeled using the genome as a template does not apply to protein glycosylation. Rather, it is necessary to quantify the glycosylation distribution at each glycosite and to aggregate this information into a population of mature glycoproteins that exist in a given biological system. To date, mass spectrometric methods for assigning singly glycosylated peptides are well-established. But it is necessary to quantify glycosylation heterogeneity accurately in order to gauge the alterations that occur during biological processes. The task is to quantify the glycosylated peptide forms as accurately as possible and then apply appropriate bioinformatics algorithms to the calculation of micro- and macro-similarities. In this review, we summarize current approaches for protein quantification as they apply to this glycoprotein similarity problem.

Glycan Compositions with GlyConnect Compozitor to Enhance Glycopeptide Identification

Glycoproteomics is unquestionably on the rise and its current development benefits from past experience in proteomics, in particular when attending to bioinformatics needs. An extensive range of software solutions is available, but the reproducibility of mass spectrometry data processing remains challenging. One of the key issues in running automated glycopeptide identification software is the selection of a reference glycan composition file. The default choices are often too broad, and a fastidious literature search to properly target this selection can be avoided. This chapter suggests the use of GlyConnect Compozitor to collect relevant information on glycosylation in a given tissue or cell line and shape an appropriate glycan composition set that can be input in the majority of search engines accommodating user-defined compositions.

SugarPy facilitates the universal, discovery-driven analysis of intact glycopeptides

MOTIVATION

Protein glycosylation is a complex post-translational modification with crucial cellular functions in all domains of life. Currently, large-scale glycoproteomics approaches rely on glycan database dependent algorithms and are thus unsuitable for discovery-driven analyses of glycoproteomes.

RESULTS

Therefore, we devised SugarPy, a glycan database independent Python module, and validated it on the glycoproteome of human breast milk. We further demonstrated its applicability by analyzing glycoproteomes with uncommon glycans stemming from the green alga Chlamydomonas reinhardtii and the archaeon Haloferax volcanii. SugarPy also facilitated the novel characterization of glycoproteins from the red alga Cyanidioschyzon merolae.

AVAILABILITY

The source code is freely available on GitHub (https://github.com/SugarPy/SugarPy), and its implementation in Python ensures support for all operating systems.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Optimal Dissociation Methods Differ for N- and O-Glycopeptides

Site-specific characterization of glycosylation requires intact glycopeptide analysis, and recent efforts have focused on how to best interrogate glycopeptides using tandem mass spectrometry (MS/MS). Beam-type collisional activation, i.e., higher-energy collisional dissociation (HCD), has been a valuable approach, but stepped collision energy HCD (sceHCD) and electron transfer dissociation with HCD supplemental activation (EThcD) have emerged as potentially more suitable alternatives. Both sceHCD and EThcD have been used with success in large-scale glycoproteomic experiments, but they each incur some degree of compromise. Most progress has occurred in the area of N-glycoproteomics. There is growing interest in extending this progress to O-glycoproteomics, which necessitates comparisons of method performance for the two classes of glycopeptides. Here, we systematically explore the advantages and disadvantages of conventional HCD, sceHCD, ETD, and EThcD for intact glycopeptide analysis and determine their suitability for both N- and O-glycoproteomic applications. For N-glycopeptides, HCD and sceHCD generate similar numbers of identifications, although sceHCD generally provides higher quality spectra. Both significantly outperform EThcD methods in terms of identifications, indicating that ETD-based methods are not required for routine N-glycoproteomics even if they can generate higher quality spectra. Conversely, ETD-based methods, especially EThcD, are indispensable for site-specific analyses of O-glycopeptides. Our data show that O-glycopeptides cannot be robustly characterized with HCD-centric methods that are sufficient for N-glycopeptides, and glycoproteomic methods aiming to characterize O-glycopeptides must be constructed accordingly.

Structural characterization and discrimination of Paris polyphylla var. yunnanensis by a molecular networking strategy coupled with ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry

RATIONALE

Paris polyphylla var. yunnanensis (Franch) Hand Mazz (PPY) is a traditional Chinese medicine with antitumor, antibacterial, hemostatic, and anthelmintic activities. Identification of the chemical composition in PPY is helpful to discover its active ingredients and can be used to establish its quality control protocols.

METHODS

The composition of PPY was identified using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry (UHPLC/QTOF-MS/MS) coupled with a molecular networking strategy. First, the UHPLC/QTOF-MS/MS approach was optimized for chemical compound profiling. Then, the MS data were processed using PeakView™ combined with an in-house database to quickly characterize the secondary metabolites. Finally, molecular networking excavated new molecular weights to discover unknown or trace natural products based on the characteristics of each cluster.

RESULTS

A total of 222 compounds, including 77 isospirostanols, 2 spirostanols, 19 furostanols, 10 pseudospirostanols, 6 cholesterols, 10 C₂₁ steroids, 5 insect metamorphosis hormones, 3 plant sterols, 6 five-ring triterpenoids, 4 flavonoids, 8 fatty acids, 2 phenylpropanoids, and 8 other compounds, were characterized in PPY by comparing their main fragmentation characteristics and pathways with the literature data, and 62 of them, 54 steroidals and 8 phenylpropanoids, were discovered or tentatively identified for the first time.

CONCLUSIONS

This study extended the application of a molecular networking strategy to traditional herbal medicines and developed a molecular networking based screening approach with a significant increase in efficiency for the discovery and identification of trace novel natural products.

An affinity chromatography and glycoproteomics workflow to profile the chondroitin sulfate proteoglycans that interact with malarial VAR2CSA in the placenta and in cancer

Chondroitin sulfate (CS) is the placental receptor for the VAR2CSA malaria protein, expressed at the surface of infected erythrocytes during Plasmodium falciparum infection. Infected cells adhere to syncytiotrophoblasts or get trapped within the intervillous space by binding to a determinant in a 4-O-sulfated CS chains. However, the exact structure of these glycan sequences remains unclear. VAR2CSA-reactive CS is also expressed by tumor cells, making it an attractive target for cancer diagnosis and therapeutics. The identities of the proteoglycans carrying these modifications in placental and cancer tissues remain poorly characterized. This information is clinically relevant since presentation of the glycan chains may be mediated by novel core proteins or by a limited subset of established proteoglycans. To address this question, VAR2CSA-binding proteoglycans were affinity-purified from the human placenta, tumor tissues and cancer cells and analyzed through a specialized glycoproteomics workflow. We show that VAR2CSA-reactive CS chains associate with a heterogenous group of proteoglycans, including novel core proteins. Additionally, this work demonstrates how affinity purification in combination with glycoproteomics analysis can facilitate the characterization of CSPGs with distinct CS epitopes. A similar workflow can be applied to investigate the interaction of CSPGs with other CS binding lectins as well.

Characterization of C. elegans Chondroitin Proteoglycans and Their Large Functional and Structural Heterogeneity; Evolutionary Aspects on Structural Differences Between Humans and the Nematode

Proteoglycans regulate important cellular pathways in essentially all metazoan organisms. While considerable effort has been devoted to study structural and functional aspects of proteoglycans in vertebrates, the knowledge of the core proteins and proteoglycan-related functions in invertebrates is relatively scarce, even for C.elegans. This nematode produces a large amount of non-sulfated chondroitin in addition to small amount of low-sulfated chondroitin chains (Chn and CS chains, respectively). Until recently, 9 chondroitin core proteins (CPGs) had been identified in C.elegans, none of which showed any homology to vertebrate counterparts or to other invertebrate core proteins. By using a glycoproteomic approach, we recently characterized the chondroitin glycoproteome of C.elegans, resulting in the identification of 15 novel CPG core proteins in addition to the 9 previously established. Three of the novel core proteins displayed homology to human proteins, indicating that CPG and CSPG core proteins may be more conserved throughout evolution than previously perceived. Bioinformatic analysis of the primary amino acid sequences revealed that the core proteins contained a broad range of functional domains, indicating that specialization of proteoglycan-mediated functions may have evolved early in metazoan evolution. This review specifically discusses our recent data in relation to previous knowledge of core proteins and GAG-attachment sites in Chn and CS proteoglycans of C.elegans and humans, and point out both converging and diverging aspects of proteoglycan evolution.

A Perspective on the Confident Comparison of Glycoprotein Site-Specific Glycosylation in Sample Cohorts

Protein glycosylation, resulting from glycosyl transferase reactions under complex control in the secretory pathway, consists of a distribution of related glycoforms at each glycosylation site. Because the biosynthetic substrate concentration and transport rates depend on architecture and other aspects of cellular phenotypes, site-specific glycosylation cannot be predicted accurately from genomic, transcriptomic, or proteomic information. Rather, it is necessary to quantify glycosylation at each protein site and how this changes among a sample cohort to provide information about disease mechanisms. At present, mature mass spectrometry-based methods allow for qualitative assignment of the glycan composition and glycosylation site of singly glycosylated proteolytic peptides. To make such quantitative comparisons, it is necessary to sample the glycosylation distribution with sufficient coverage and accuracy for confident assessment of the glycosylation changes that occur in the biological cohort. In this Perspective, we discuss the unmet needs for mass spectrometry acquisition methods and bioinformatics for the confident comparison of protein site-specific glycosylation among sample cohorts.

Recent advances in mass spectrometry (MS)-based glycoproteomics in complex biological samples

Protein glycosylation plays a key role in various biological processes and disease-related pathological progression. Mass spectrometry (MS)-based glycoproteomics is a powerful approach that provides a system-wide profiling of the glycoproteome in a high-throughput manner. There have been numerous significant technological advances in this field, including improved glycopeptide enrichment, hybrid fragmentation techniques, emerging specialized software packages, and effective quantitation strategies, as well as more dedicated workflows. With increasingly sophisticated glycoproteomics tools on hand, researchers have extensively adapted this approach to explore different biological systems both in terms of in-depth glycoproteome profiling and comparative glycoproteome analysis. Quantitative glycoproteomics enables researchers to discover novel glycosylation-based biomarkers in various diseases with potential to offer better sensitivity and specificity for disease diagnosis. In this review, we present recent methodological developments in MS-based glycoproteomics and highlight its utility and applications in answering various questions in complex biological systems.

Characterization of Cell Glycocalyx with Mass Spectrometry Methods

The cell membrane plays an important role in protecting the cell from its extracellular environment. As such, extensive work has been devoted to studying its structure and function. Crucial intercellular processes, such as signal transduction and immune protection, are mediated by cell surface glycosylation, which is comprised of large biomolecules, including glycoproteins and glycosphingolipids. Because perturbations in glycosylation could result in dysfunction of cells and are related to diseases, the analysis of surface glycosylation is critical for understanding pathogenic mechanisms and can further lead to biomarker discovery. Different mass spectrometry-based techniques have been developed for glycan analysis, ranging from highly specific, targeted approaches to more comprehensive profiling studies. In this review, we summarized the work conducted for extensive analysis of cell membrane glycosylation, particularly those employing liquid chromatography with mass spectrometry (LC-MS) in combination with various sample preparation techniques.

Isolation and characterization of glycosylated neuropeptides

Glycosylation is one of the most ubiquitous and complex post-translational modifications (PTMs). It plays pivotal roles in various biological processes. Studies at the glycopeptide level are typically considered as a downstream work resulting from enzymatic digested glycoproteins. Less attention has been focused on glycosylated endogenous signaling peptides due to their low abundance, structural heterogeneity and the lack of enabling analytical tools. Here, protocols are presented to isolate and characterize glycosylated neuropeptides utilizing nanoflow liquid chromatography coupled with mass spectrometry (LC-MS). We first demonstrate how to extract neuropeptides from raw tissues and perform further separation/cleanup before MS analysis. Then we describe hybrid MS methods for glycosylated neuropeptide profiling and site-specific analysis. We also include recommendations for data analysis to identify glycosylated neuropeptides in crustaceans where a complete neuropeptide database is still lacking. Other strategies and future directions are discussed to provide readers with alternative approaches and further unravel biological complexity rendered by glycosylation.

DecoyDeveloper: An On-Demand, De Novo Decoy Glycopeptide Generator

Glycopeptide analysis is a growing field that is struggling to adopt effective, automated tools. Many creative workflows and software apps have emerged recently that offer promising capabilities for assigning glycopeptides to MS data in an automated fashion. The effectiveness of these tools is best measured and improved by determining how often they would select a glycopeptide decoy as a spectral match, instead of its correct assignment; yet generating the appropriate number and type of glycopeptide decoys can be challenging. To address this need, we have designed DecoyDeveloper, an on-demand decoy glycopeptide generator that can produce a high volume of decoys with low mass differences. DecoyDeveloper has a simple user interface and is capable of producing large sets of decoys containing complete, biologically relevant glycan and peptide sequences. We demonstrate the tool's efficiency by applying it to a set of 80 glycopeptide targets. This tool is freely available and can be found at http://glycopro.chem.ku.edu/J1.php .

Synthetic standard aided quantification and structural characterization of amyloid-beta glycopeptides enriched from cerebrospinal fluid of Alzheimer's disease patients

An early pathological hallmark of Alzheimer’s disease (AD) is amyloid-β (Aβ) deposits in the brain, which largely consist of up to 43 amino acids long Aβ peptides derived from the amyloid precursor protein (APP). We previously identified a series of sialylated Tyr-10 O-glycosylated Aβ peptides, 15–20 residues long, from human cerebrospinal fluid (CSF) and observed a relative increase of those in AD vs non-AD patients. We report here on the synthesis and use of an isotopically double-labeled Aβ1-15 glycopeptide, carrying the core 1 Galβ3GalNAcα1-O-Tyr-10 structure, to (1) identify by HCD LC-MS/MS the definite glycan core 1 structure of immunopurified and desialylated Aβ glycopeptides in human CSF and to (2) establish a LC-MS/MS quantification method for desialylated Aβ1-15 (and Aβ1-17) glycopeptides and to (3) compare the concentrations of these Aβ glycopeptides in CSF from 20 AD patients and 20 healthy controls. Although we unambiguously identified the core 1 structures and Tyr-10 attachment sites of the glycopeptides, we did not observe any quantitative differences, determined through both peptide and oxonium ion fragments, of the desialylated Aβ1-15 or Aβ1-17 glycopeptides between the AD and non-AD group. The new quantitative glycoproteomic approach described, using double-labeled glycopeptide standards, will undoubtedly facilitate future studies of glycopeptides as clinical biomarkers but should also embrace sialylated Aβ standards to reveal specific sialylation patterns of individual Aβ glycopeptides in AD patients and controls.

Advances in mass spectrometry-based glycoproteomics

Protein glycosylation, an important PTM, plays an essential role in a wide range of biological processes such as immune response, intercellular signaling, inflammation, and host-pathogen interaction. Aberrant glycosylation has been correlated with various diseases. However, studying protein glycosylation remains challenging because of low abundance, microheterogeneities of glycosylation sites, and poor ionization efficiency of glycopeptides. Therefore, the development of sensitive and accurate approaches to characterize protein glycosylation is crucial. The identification and characterization of protein glycosylation by MS is referred to as the field of glycoproteomics. Methods such as enrichment, metabolic labeling, and derivatization of glycopeptides in conjunction with different MS techniques and bioinformatics tools, have been developed to achieve an unequivocal quantitative and qualitative characterization of glycoproteins. This review summarizes the recent developments in the field of glycoproteomics over the past 6 years (2012 to 2018).

Data-independent oxonium ion profiling of multi-glycosylated biotherapeutics

The characterization of glycosylation is required for many protein therapeutics. The emergence of antibody and antibody-like molecules with multiple glycan attachment sites has rendered glycan analysis increasingly more complicated. Reliance on site-specific glycopeptide analysis is therefore necessary to fully analyze multi-glycosylated biotherapeutics. Established glycopeptide methodologies have generally utilized a priori knowledge of the glycosylation states of the investigated protein(s), database searching of results generated from data-dependent liquid chromatography–tandem mass spectrometry workflows, and extracted ion quantitation of the individual identified species. However, the inherent complexity of glycosylation makes predicting all glycoforms on all glycosylation sites extremely challenging, if not impossible. That is, only the “knowns” are assessed. Here, we describe an agnostic methodology to qualitatively and quantitatively assess both “known” and “unknown” site-specific glycosylation for biotherapeutics that contain multiple glycosylation sites. The workflow uses data-independent, all ion fragmentation to generate glycan oxonium ions, which are then extracted across the entirety of the chromatographic timeline to produce a glycan-specific “fingerprint” of the glycoprotein sample. We utilized both HexNAc and sialic acid oxonium ion profiles to quickly assess the presence of Fab glycosylation in a therapeutic monoclonal antibody, as well as for high-throughput comparisons of multi-glycosylated protein drugs derived from different clones to a reference product. An automated method was created to rapidly assess oxonium profiles between samples, and to provide a quantitative assessment of similarity.

Effective Assignment of α2,3/α2,6-Sialic Acid Isomers by LC-MS/MS-Based Glycoproteomics

Distinct structural changes of the α2,3/α2,6-sialic acid glycosidic linkages on glycoproteins are of importance in cancer biology, inflammatory diseases, and virus tropism. Current glycoproteomic methodologies are, however, not amenable toward high-throughput characterization of sialic acid isomers. To enable such assignments, a mass spectrometry method utilizing synthetic model glycopeptides for the analysis of oxonium ion intensity ratios was developed. This method was successfully applied in large-scale glycoproteomics, thus allowing the site-specific structural characterization of sialic acid isomers.

The heparan sulfate proteoglycan grip on hyperlipidemia and atherosclerosis

Heparan sulfate proteoglycans are found at the cell surface and in the extracellular matrix, where they interact with a plethora of proteins involved in lipid homeostasis and inflammation. Over the last decade, new insights have emerged regarding the mechanism and biological significance of these interactions in the context of cardiovascular disease. The majority of cardiovascular disease-related deaths are caused by complications of atherosclerosis, a disease that results in narrowing of the arterial lumen, thereby reducing blood flow to critical levels in vital organs, such as the heart and brain. Here, we discuss novel insights into how heparan sulfate proteoglycans modulate risk factors such as hyperlipidemia and inflammation that drive the initiation and progression of atherosclerotic plaques to their clinical critical endpoint.

LC-MS/MS characterization of xyloside-primed glycosaminoglycans with cytotoxic properties reveals structural diversity and novel glycan modifications

Structural characterization of glycosaminoglycans remains a challenge but is essential for determining structure-function relationships between glycosaminoglycans and the biomolecules with which they interact and for gaining insight into the biosynthesis of glycosaminoglycans. We have recently reported that xyloside-primed chondroitin/dermatan sulfate derived from a human breast carcinoma cell line, HCC70, has cytotoxic effects and shown that it differs in disaccharide composition from nontoxic chondroitin/dermatan sulfate derived from a human breast fibroblast cell line, CCD-1095Sk. To further investigate the structural requirements for the cytotoxic effect, we developed a novel LC-MS/MS approach based on reversed-phase dibutylamine ion-pairing chromatography and negative-mode higher-energy collision dissociation and used it in combination with cell growth studies and disaccharide fingerprinting. This strategy enabled detailed structural characterization of linkage regions, internal oligosaccharides, and nonreducing ends, revealing not only differences between xyloside-primed chondroitin/dermatan sulfate from HCC70 cells and CCD-1095Sk cells, but also sialylation of the linkage region and previously undescribed methylation and sulfation of the nonreducing ends. Although the xyloside-primed chondroitin/dermatan sulfate from HCC70 cells was less complex in terms of presence and distribution of iduronic acid than that from CCD-1095Sk cells, both glucuronic acid and iduronic acid appeared to be essential for the cytotoxic effect. Our data have moved us one step closer to understanding the structure of the cytotoxic chondroitin/dermatan sulfate from HCC70 cells primed on xylosides and demonstrate the suitability of the LC-MS/MS approach for structural characterization of glycosaminoglycans.

Mass Spectrometry Approaches to Glycomic and Glycoproteomic Analyses

Glycomic and glycoproteomic analyses involve the characterization of oligosaccharides (glycans) conjugated to proteins. Glycans are produced through a complicated nontemplate driven process involving the competition of enzymes that extend the nascent chain. The large diversity of structures, the variations in polarity of the individual saccharide residues, and the poor ionization efficiencies of glycans all conspire to make the analysis arguably much more difficult than any other biopolymer. Furthermore, the large number of glycoforms associated with a specific protein site makes it more difficult to characterize than any post-translational modification. Nonetheless, there have been significant progress, and advanced separation and mass spectrometry methods have been at its center and the main reason for the progress. While glycomic and glycoproteomic analyses are still typically available only through highly specialized laboratories, new software and workflow is making it more accessible. This review focuses on the role of mass spectrometry and separation methods in advancing glycomic and glycoproteomic analyses. It describes the current state of the field and progress toward making it more available to the larger scientific community.

Large-scale intact glycopeptide identification by Mascot database search

Workflows capable of determining glycopeptides in large-scale are missing in the field of glycoproteomics. We present an approach for automated annotation of intact glycopeptide mass spectra. The steps in adopting the Mascot search engine for intact glycopeptide analysis included: (i) assigning one letter codes for monosaccharides, (ii) linearizing glycan sequences and (iii) preparing custom glycoprotein databases. Automated annotation of both N- and O-linked glycopeptides was proven using standard glycoproteins. In a large-scale study, a total of 257 glycoproteins containing 970 unique glycosylation sites and 3447 non-redundant N-linked glycopeptide variants were identified in 24 serum samples. Thus, a single tool was developed that collectively allows the (i) elucidation of N- and O-linked glycopeptide spectra, (ii) matching glycopeptides to known protein sequences, and (iii) high-throughput, batch-wise analysis of large-scale glycoproteomics data sets.

Expanding the chondroitin glycoproteome of Caenorhabditis elegans

Chondroitin sulfate proteoglycans (CSPGs) are important structural components of connective tissues in essentially all metazoan organisms. In vertebrates, CSPGs are involved also in more specialized processes such as neurogenesis and growth factor signaling. In invertebrates, however, knowledge of CSPGs core proteins and proteoglycan-related functions is relatively limited, even for Caenorhabditis elegans. This nematode produces large amounts of non-sulfated chondroitin in addition to low-sulfated chondroitin sulfate chains. So far, only nine core proteins (CPGs) have been identified, some of which have been shown to be involved in extracellular matrix formation. We recently introduced a protocol to characterize proteoglycan core proteins by identifying CS-glycopeptides with a combination of biochemical enrichment, enzymatic digestion, and nano-scale liquid chromatography MS/MS analysis. Here, we have used this protocol to map the chondroitin glycoproteome in C. elegans, resulting in the identification of 15 novel CPG proteins in addition to the nine previously established. Three of the newly identified CPGs displayed homology to vertebrate proteins. Bioinformatics analysis of the primary protein sequences revealed that the CPG proteins altogether contained 19 unique functional domains, including Kunitz and endostatin domains, suggesting direct involvement in protease inhibition and axonal migration, respectively. The analysis of the core protein domain organization revealed that all chondroitin attachment sites are located in unstructured regions. Our results suggest that CPGs display a much greater functional and structural heterogeneity than previously appreciated and indicate that specialized proteoglycan-mediated functions evolved early in metazoan evolution.

Glycoforest 1.0

Tandem mass spectrometry, when combined with liquid chromatography and applied to complex mixtures, produces large amounts of raw data, which needs to be analyzed to identify molecular structures. This technique is widely used, particularly in glycomics. Due to a lack of high throughput glycan sequencing software, glycan spectra are predominantly sequenced manually. A challenge for writing glycan-sequencing software is that there is no direct template that can be used to infer structures detectable in an organism. To help alleviate this bottleneck, we present Glycoforest 1.0, a partial de novo algorithm for sequencing glycan structures based on MS/MS spectra. Glycoforest was tested on two data sets (human gastric and salmon mucosa O-linked glycomes) for which MS/MS spectra were annotated manually. Glycoforest generated the human validated structure for 92% of test cases. The correct structure was found as the best scoring match for 70% and among the top 3 matches for 83% of test cases. In addition, the Glycoforest algorithm detected glycan structures from MS/MS spectra missing a manual annotation. In total 1532 MS/MS previously unannotated spectra were annotated by Glycoforest. A portion containing 521 spectra was manually checked confirming that Glycoforest annotated an additional 50 MS/MS spectra overlooked during manual annotation.

Recent advances in mass spectrometric analysis of glycoproteins

Glycosylation is one of the most common posttranslational modifications of proteins that plays essential roles in various biological processes, including protein folding, host-pathogen interaction, immune response, and inflammation and aberrant protein glycosylation is a well-known event in various disease states including cancer. As a result, it is critical to develop rapid and sensitive methods for the analysis of abnormal glycoproteins associated with diseases. Mass spectrometry (MS) in conjunction with different separation methods, such as capillary electrophoresis (CE), ion mobility (IM), and high performance liquid chromatography (HPLC) has become a popular tool for glycoprotein analysis, providing highly informative fragments for structural identification of glycoproteins. This review provides an overview of the developments and accomplishments in the field of glycomics and glycoproteomics reported between 2014 and 2016.

Chemical Glycoproteomics

Chemical tools have accelerated progress in glycoscience, reducing experimental barriers to studying protein glycosylation, the most widespread and complex form of posttranslational modification. For example, chemical glycoproteomics technologies have enabled the identification of specific glycosylation sites and glycan structures that modulate protein function in a number of biological processes. This field is now entering a stage of logarithmic growth, during which chemical innovations combined with mass spectrometry advances could make it possible to fully characterize the human glycoproteome. In this review, we describe the important role that chemical glycoproteomics methods are playing in such efforts. We summarize developments in four key areas: enrichment of glycoproteins and glycopeptides from complex mixtures, emphasizing methods that exploit unique chemical properties of glycans or introduce unnatural functional groups through metabolic labeling and chemoenzymatic tagging; identification of sites of protein glycosylation; targeted glycoproteomics; and functional glycoproteomics, with a focus on probing interactions between glycoproteins and glycan-binding proteins. Our goal with this survey is to provide a foundation on which continued technological advancements can be made to promote further explorations of protein glycosylation.